Adaptive Impedance Modulation-Based Control for Human-Robot Interaction

Impedance control is commonly used to garantee the effciency and safety of physical human-robot interaction. Classic impedance control is not able to adaptivly modify impedance parameters according to dynamic enviroment. This paper used adaptive learning algorithm to modify parameters according human and enviroment variation. Model of robot and impedance control are established and corresponding experiments are conducted to verify the performancec of proposed approach. The simulation and experiment results indicated that the proposed approach can achieve a better convergence speed and robustness.